The principles of evidence-based medicine (EBM) are the foundation of modern medical practice. Surgeons are familiar with the commonly used statistical techniques to test hypotheses, summarize findings, and provide answers within a specified range of probability. Based on this knowledge, they are able to critically evaluate research before deciding whether or not to adopt the findings into practice. Recently, there has been an increased use of artificial intelligence (AI) to analyze information and derive findings in orthopaedic research. These techniques use a set of statistical tools that are increasingly complex and may be unfamiliar to the orthopaedic surgeon. It is unclear if this shift towards less familiar techniques is widely accepted in the orthopaedic community. This study aimed to provide an exploration of understanding and acceptance of AI use in research among orthopaedic surgeons. Semi-structured in-depth interviews were carried out on a sample of 12 orthopaedic surgeons. Inductive thematic analysis was used to identify key themes.Aims
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Distraction osteogenesis with intramedullary lengthening devices has undergone rapid development in the past decade with implant enhancement. In this first single-centre matched-pair analysis we focus on the comparison of treatment with the PRECICE and STRYDE intramedullary lengthening devices and aim to clarify any clinical and radiological differences. A single-centre 2:1 matched-pair retrospective analysis of 42 patients treated with the STRYDE and 82 patients treated with the PRECICE nail between May 2013 and November 2020 was conducted. Clinical and lengthening parameters were compared while focusing radiological assessment on osseous alterations related to the nail’s telescopic junction and locking bolts at four different stages.Aims
Methods
This study assesses patient barriers to successful telemedicine care in orthopaedic practices in a large academic practice in the COVID-19 era. In all, 381 patients scheduled for telemedicine visits with three orthopaedic surgeons in a large academic practice from 1 April 2020 to 12 June 2020 were asked to participate in a telephone survey using a standardized Institutional Review Board-approved script. An unsuccessful telemedicine visit was defined as patient-reported difficulty of use or reported dissatisfaction with teleconferencing. Patient barriers were defined as explicitly reported barriers of unsatisfactory visit using a process-based satisfaction metric. Statistical analyses were conducted using analysis of variances (ANOVAs), ranked ANOVAs, post-hoc pairwise testing, and chi-squared independent analysis with 95% confidence interval.Aims
Methods
Restarting planned surgery during the COVID-19 pandemic is a clinical and societal priority, but it is unknown whether it can be done safely and include high-risk or complex cases. We developed a Surgical Prioritization and Allocation Guide (SPAG). Here, we validate its effectiveness and safety in COVID-free sites. A multidisciplinary surgical prioritization committee developed the SPAG, incorporating procedural urgency, shared decision-making, patient safety, and biopsychosocial factors; and applied it to 1,142 adult patients awaiting orthopaedic surgery. Patients were stratified into four priority groups and underwent surgery at three COVID-free sites, including one with access to a high dependency unit (HDU) or intensive care unit (ICU) and specialist resources. Safety was assessed by the number of patients requiring inpatient postoperative HDU/ICU admission, contracting COVID-19 within 14 days postoperatively, and mortality within 30 days postoperatively.Aims
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The primary aim was to assess the rate of patient deferral of elective orthopaedic surgery and whether this changed with time during the coronavirus disease 2019 (COVID-19) pandemic. The secondary aim was to explore the reasons why patients wanted to defer surgery and what measures/circumstances would enable them to go forward with surgery. Patients were randomly selected from elective orthopaedic waiting lists at three centres in the UK in April, June, August, and September 2020 and were contacted by telephone. Patients were asked whether they wanted to proceed or defer surgery. Patients who wished to defer were asked seven questions relating to potential barriers to proceeding with surgery and were asked whether there were measures/circumstances that would allow them to go forward with surgery.Aims
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Aims. The use of technology to assess balance and alignment during total knee surgery can provide an overload of numerical data to the surgeon. Meanwhile, this quantification holds the potential to clarify and guide the surgeon through the surgical decision process when selecting the appropriate bone recut or soft tissue adjustment when balancing a total knee. Therefore, this paper evaluates the potential of deploying supervised machine learning (ML) models to select a surgical correction based on